Detectability of Crack Lengths from Acoustic Emissions Using Physics of Wave Propagation in Plate Structures

J Nondestruct Eval (2017) 36:41 DOI 10.1007/s10921-017-0392-x Detectability of Crack Lengths from Acoustic Emissions Using Physics of Wave Propagation in Plate Structures Banibrata Poddar 1 Victor Giurgiutiu 2 Received: 11 August 2016 / Accepted: 15 January 2017 Notwithstanding the Copyright Transfer Statement, Author retains the copyright on some/all illustrations contained within the article 2017 Abstract This paper presents a study to understand the physical nature of fatigue crack growth as an acoustic emission source and detectability of the crack length form the recorded acoustic emission signal in plate structures. For most of the thin walled engineering structures, the acoustic emission detection through sensor network has been well established. However, the majority of the research is focused on prediction of the acoustic emission due to fatigue crack growth using stochastic methods. Where, stochastic models are used to predict the criticality of the damage. The scope of this research is to use predictive simulation method for acoustic emission signals and extract the damage related information from acoustic emission signals based on physics of material. This approach is in contrast with the traditional approach involving statistics of acoustic emissions and their relation with damage criticality. In this article, first, we present our approach to understand fatigue crack growth as source of acoustic emission using physics of guided wave propagation in FEM. Then, using this physical understanding, we present our investigation on detectability of crack lengths directly from crack-generated acoustic emission signals. Finally, we present our method to extract fatigue crack length information from acoustic emission signals recorded during fatigue crack growth. B Banibrata Poddar bpoddar@i-a-i.com 1 Intelligent Automation Inc., 15400 Calhoun Dr, Rockville, MD 20855, USA 2 Department of Mechanical Engineering, University of South Carolina, 300 Main Street, Columbia, SC 29208, USA 1 State of the Art Passive detection of fatigue cracks by sensing acoustic emission (AE) has attracted attention of many researchers for decades. To extract crack related acoustic emission data from recorded AE signals, researchers have applied data driven methods [1 4]. One of the most critical damages studied is a fatigue crack. However, it is important to develop science and understanding of crack-generated acoustic emission (AE) wave signals to successfully identify acoustic emission due to crack growth using passive sensing mode. To develop this understanding, researchers have studied acoustic emission (AE) due to crack propagation in elastic medium [5,6]. Ceranogliu and Yih-Hsing [7] have analyzed generation of transient waves by variety of dynamic nuclei of strains based on generalized ray theory. Chung and Kannatey-Asibu [8] have studied acoustic emission due to plastic deformation in a pure crystals considering acceleration of a moving dislocation. Lysak [9] investigated acoustic emission from a growing crack by formulating non-stationary dynamic problems of crack theory. Lysak obtained variety of new analytical relationship between crack parameters and AE signal parameters. Andreykiv et al. [10,11] have studied acoustic emission caused by internal crack growth. Sause and Richler have studied cracks as source of AE using cohesive zone approach in FEM [12]. In another work Sause and Horn [13] haveproposed a microscopic source model to simulate AE in CFRP. González and LLorca [14] have used multiscale modeling to capture the fracture behavior of fiber reinforced composite. Other researchers have used peridynamic formulation based on homogenization and mapping between elastic and fracture parameters of the micro-scale peridynamic bonds and the macro-scale parameters of the composite [15]. Several studies are also performed to understand the emission of guided waves such as, Lamb waves, due to crack growth in

41 Page 2 of 13 J Nondestruct Eval (2017) 36:41 plate like structures [16]. Gorman and Prosser [17] suggested the application of normal mode expansion. Maji et al. [18] have demonstrated the use of NDE technique based on Lamb wave propagation to locate the source of acoustic emissions. Prosser et al. [19] used Mindlin plate theory and finite element analysis to model acoustic emissions. Zhou and Zhang [20] have studied the use of phase difference of the received signal at two different sensor locations to locate AE source in a thick plate. Use of acoustic emission for detecting and locating fatigue cracks in metallic structures is widely reported but studies to estimate crack length from acoustic emission are rare. Lysak have demonstrated a relationship between the experimental AE count and theoretical stress intensity factor [21]. In other experimental study researchers aimed to find relationship between AE energy and fracture energy in concrete [22,23]. Gagar et al. [3] have developed a method for deducing crack length based on correlations between AE signals generated during fatigue crack growth and corresponding cyclic loads. The methods of estimating crack length reported in the literature are based on parametric relationship of AE and fracture mechanics [24]. These methods reply on experiment driven models. In this paper we present our work aimed towards estimation of crack length based on physics of wave propagation in plate structures due to crack growth. There are two fundamental stages of generation of acoustic energy and a crack growth due to material failure [9]; first the failure of the material and formation of new crack surfaces and then, the propagation of the resulting temporal displacement field as acoustic waves. Lysak have [9] have proposed an analytical approach to address the generation of this acoustic waves due to material failure using the theory of fracture mechanics and wave propagation. This model is good for explaining the generation of the acoustic energy due to material failure. However, the propagation of the generated acoustic wave through the plate waveguide with a crack is a very complex wave guide problem for an analytical model. The approach presented by Sause s [25] relies on finite element method to solve the wave guide problem where a failure criterion is defined for the initiation of crack and the resulting temporal displacement field was calculated. This approach is again focused on the generation of acoustic emission from the crack tip. However, the dynamics of a growing crack and its characteristics as a wave source have not been studied before. The aim of this research is to develop an understanding of the characteristics of a fatigue crack as a guided wave source. This understanding will help us predict crack lengths from acoustic emissions (AE) in plate structures. For simplicity of simulation, we approximated the source at the crack tip as an extended source [12] using the method proposed by Hamstad et al. [26]. In this study we focused on the dynamics of the crack as an AE source rather than the generation of acoustic energy due to the material failure at the crack tip. We performed FE analysis along with experimental studies. First, we introduce the experimental procedure and present detailed 3D FE models. Then, we elaborate physical phenomenon to be used to estimate the crack length from recorded AE signal. Subsequently, we present experimental validation of our method. Finally, we present our attempt to apply this method to detect fatigue crack length during fatigue test followed by conclusion. 2 FE Simulation of Acoustic Emissions in a Plate from Fatigue Experiment Our aim is to simulate acoustic emission recorded during uniaxial tensile fatigue test. For generation of AE signals we use 1 mm thick Al2024 specimens with a 1 mm hole at the center. We assume that the specimen is under pure tension and the crack growth is through the thickness of the plate along the plate surface. Therefore, we also assume symmetric emission of acoustic energy across the plate thickness (Fig. 1). We used Fig. 1 a Schematic of the fatigue crack growth, b fatigue crack in the actual specimen

J Nondestruct Eval (2017) 36:41 Page 3 of 13 41 Fig. 2 Time and frequency characteristics of dipole as acoustic emission source 3D FE model of the plate to capture the effects of the crack on the acoustic emission. Dynamic finite-element modeling requires that the element size must be smaller than the smallest wavelength of interest, and the time step must satisfy a stability condition called the Courant Friedrichs Lewy (CFL) condition. In our case the CFL condition requires the time step to be less than the time required for the bulk longitudinal wave to traverse a single element. This means the smaller the element size the smaller the time step should be. Due to limitation on simulation capability, we choose element size of 0.25 mm for our simulation. For AL2024T4 with bulk longitudinal wave speed of 6.2 mm/μs, we need a time step of 40 ns or less to satisfy the CFL condition. But, because of limitation on computational resources, we are able to simulate at CFL = 3 for the source rise time of 1.5 μs with half cycle cosine (Fig. 2). Following Hamstad et al.[26], this also gives us minimum wavelength λ m = 4.71 mm. We use λ/s = 9.4, λ/cs = 18.8, D/s = 40 (where, s, cs, and D are element size, dipole size and the distance between the source and sensor) which according to Hamstad et al. [26] should give satisfactory result for acoustic emission simulation. To create a 3D FEM model of a fatigue crack in a plate, we idealize a fatigue butterfly-crack in our specimen shown in Fig. 1b. We assume crack surfaces to be perpendicular to the plate surface and radiating outwards from the hole. We also assume crack surfaces to be stress free. We place the acoustic emission sources at the tips of the cracks. We extend the point source model [26] to a line source by distributing point sources along a line. We model the source as equal strength dipoles distributed across the thickness of the plate (Fig. 3) approximating to a line source of acoustic emission. Also, we place these dipoles at both the ends of the elements at the crack tips to approximate AE due to crack growth of one element length (0.25 mm). This makes the AE source as an extended source instead of a point source [12] By incorporating a temporal variation of the dipole strength, we simulate generation of acoustic emission from Fig. 3 a Dipoles at crack tips for simulation of acoustic emission due to crack growth of one element length; b distribution of dipoles across the thickness of the plate the crack tips. As mentioned earlier, following Hamstad et al.[26], we use the temporal variation of the dipole strength as a cosine bell curve with 1.5 µs rise time. Figure 4 shows a schematic diagram of the FEM model created for simulation of acoustic emission in 3D. To minimize boundary reflections from the edges of the FE model, we use non-reflecting boundaries (NRB) around the edges.

41 Page 4 of 13 J Nondestruct Eval (2017) 36:41 Nonreflecting Boundary Width Sensor L Nonreflecting Boundary AE Sources Fig. 4 Schematic diagram of 3D FE model for acoustic emission from crack tips The NRBs are created by adding damping elements on top and bottom surfaces of the plate around the edges and at the edge of the boundaries [27]. We increase the damping coefficients of these damping elements along the length of the NRB starting from zero to a finite value [27]. This is done to minimize the reflection of wave energy from the edge of the NRB. It has been shown that this type of NRBs are more effective in reducing the edge reflections in a plate structures [27]. The purpose of NRBs is to absorb the incident and reflected wave energies to minimize boundary reflections. Figure 5a and (b) show out of plane displacements at 20 mm from the hole along the length of the specimen from FE model without NRB and with NRB. We can see that the boundary reflections are almost eliminated by the use of NRB. The usefulness of NRB is also clear from Fig. 6a and b which show the time frequency analysis of the displacement plots shown in Fig. 5. However, the NRBs do not eliminate boundary reflections completely. From Fig. 5b, we can see that the ripples after the arrival of the first acoustic emission changes as the specimen dimensions are changed. This is the effect of specimen geometry on the acoustic emission signal due to reminiscent boundary reflections. But, these reflections are much smaller than the direct acoustic emission signal and contain only very low frequencies as shown in Fig. 6b. Therefore, we conclude that, NRBs are effective in simulating acoustic emissions using small 3D FE models for efficient simulation. To further investigate effects of the presence of the butterfly crack, we create another FE model with the identical geometry with no crack. We place the dipoles at the same locations relative to the hole. The purpose of this study is to understand if there is a difference in the acoustic emission signal due to the presence of the crack and if this difference is related to the crack geometry. Fig. 5 Out of plane displacement at 20 mm from hole a without NRB, b with NRB Fig. 6 Time-frequency analysis of out of plane displacement at 20 mm from hole a without NRB, b with NRB

J Nondestruct Eval (2017) 36:41 Page 5 of 13 41 Fig. 7 Out of plane displacement at 20 mm from hole 1 0.8 Normalized Amplitude 0.6 0.4 0.2 0-0.2-0.4 0 5 10 15 20 25 Time, µs Fig. 8 Frequency content of out of plane displacement at 20 mm from hole Figure 7 shows the comparison between the out of plane displacement calculated by the two FE models; one is with butterfly cracks and the other is without. From the time variation of the displacements, we can clearly see that there is a significant difference due to the presence of the crack. Figure 8 shows the calculated displacements in frequency domain. We can see that the presence of the butterfly cracks modifies the frequency content of the acoustic emission signal significantly. Therefore, the crack acts as a frequency filter to the acoustic emission. It is apparent that, at least theoretically, a significant difference exists between the crack related acoustic emission and non-crack related acoustic emission. 3 Resonance of Fatigue Crack Due to Fatigue Crack Growth As presented in the previous section, the presence of the crack modifies the frequency content to the acoustic emission signal received. Next, we investigate the possibility of extracting crack features from acoustic emission. First, we perform harmonic analysis on 3D FE models. On the model with crack, instead of performing transient analysis with time varying dipole strengths, we performed harmonic analysis with dipole strengths being constant with frequency. The aim is to understand the dynamics of the crack vibration. Figure 9 shows that due to a harmonic source at the crack tip, the crack undergoes resonances in crack-opening type motion. Also, it shows that the resonance frequency will depend on the length of the crack. For example, the fundamental resonance frequency of a 2 mm long crack is higher than that of a 5 mm long crack; as the crack length increases, the fundamental resonance frequency will decrease. It is important to note that, this is an extended source type model as described by Sause et al. [12]. Therefore, the prediction of the FE simulation is reliable when the size of a crack is much larger than the thickness of the plate as well as the increase in crack length. For this case the size of the crack (4 mm) is much larger than the thickness of the plate (1 mm) and the increase in crack length simulated (0.25 mm). Figure 10 shows the frequency content of the simulated acoustic emission in terms of out of plane displacement mea-

41 Page 6 of 13 J Nondestruct Eval (2017) 36:41 Fig. 9 Crack opening resonance frequencies from harmonic analysis Fig. 10 Crack resonance captured from an acoustic emission signal measured at a distance sured at 20 mm away from the hole. We can clearly see multiple resonances from the simulated acoustic emission signal. Upon comparing Figs. 9 and 10, we can see that these resonance frequencies are same as the resonance frequencies associated with the crack opening motion. Therefore, we confirm through simulation that a wideband acoustic source located at the tip of a crack causes the crack to resonate and this resonance can be detected from the acoustic emission signal at a distance from the crack. Since the crack resonance frequency depends on the crack length, theoretically it is possible to detect crack length from the acoustic emission signals. The correlation of the crack length with the resonance frequency can be obtained by FE models similar to the ones presented. 4 Experimental Validation of the Resonance Phenomenon Our aim is to validate the simulation results with a fatigue test experiment. During fatigue tests, when the crack grows, the plate causes acoustic emissions from one of the crack tips. In our simulation, the crack surfaces are assumed to be stress free which is not the case in a fatigue crack. Therefore, to confirm the phenomenon of crack resonance due an acoustic emission source at the tip, we use a slit instead of a fatigue crack. We start with a large aluminum plate with 1220 mm in length and 1220 mm in width and 1.6 mm thick to avoid boundary reflections. We cut a through thickness slit in the plate with diamond cutting disc of 0.25 mm in thickness as shown in Figs. 11 and 12a. Then, piezoelectric wafer active sensors (PWAS) are bonded at one of the tips of the slit to emulate an acoustic source [28]. Two PWAS transducers are bonded at the slit tip on the top and bottom surfaces of the plate. The advantage of using a PWAS in this configuration is in its excitability. We can excite the PWAS transducers in-phase or out-of-phase. However, in our fatigue test, we load the plate under uniform tension which, in our understanding, will cause symmetric type excitation at the crack when the crack grows. Therefore, we excite the PWAS transducers simultaneously in-phase to cause a symmetric excitation. To create a wideband acoustic emission, we excite the PWAS transducers with a voltage pulse as shown in Fig. 12b and c.

J Nondestruct Eval (2017) 36:41 Page 7 of 13 41 source at the crack tip using FE analysis and experiments. As acoustic emissions are wideband excitations generally at the crack tip, our aim is to use this phenomenon to detect fatigue crack length from recorded acoustic emission signal. There are two main mechanisms for generation of acoustic emission from a fatigue crack as shown in Fig. 14. As shown on the left branch of Fig. 14, one mechanism is when the crack grows and some of the energy at the crack tip is released in the form of acoustic emission [29]. The other mechanism is depicted on the right branch of Fig. 14; when the crack resonated due to ambient vibration, the rubbing of the crack surfaces create acoustic emissions [30]. Our main challenge is to detect these acoustic emissions and identify crack resonance from them. We follow the left branch in Fig. 14 to investigate acoustic emissions due to fatigue crack growth. 6 Identification of Crack Length from Acoustic Emission Due to Crack Growth Fig. 11 Schematic diagram of experiment to detect resonance of a slit caused by an acoustic source at tip The resulted acoustic emission is measured 20 mm from the slit with a LASER doppler velocimeter (LDV). Figure 13a shows the frequency domain plot of the measured acoustic emission at 20 mm from the slit; in this figure, we can see multiple peaks which look like resonances. To verify these peaks, we also scan the area around crack using LDV to visualize the wave field around the crack. This is done by using chirp excitation with synchronized LDV measurement at a large number of points around the slit. This measurement makes it possible to visualize resonances of the slit due to the acoustic emission from PWAS. Figure 13b e show the plate surface velocity around the slit measured by LDV at various resonance frequencies. Upon comparison with Fig. 13a, we can clearly understand that the resonance peaks in Fig. 13a correspond to the resonance at the through thickness slit. This experiment confirms the crack resonance due to acoustic emission from its tip and validates our FE analysis. 5 Detection of Fatigue Crack Length from Acoustic Emission Signals Previous sections proposed and validated the phenomenon of crack vibration due the presence of a wideband acoustic It is important to minimize the boundary reflections to successfully extract crack information from acoustic emission. To minimize boundary reflection in a small specimen, we use absorbing clay around the boundary (Fig. 15a, b).the length, width, and thickness of the specimen are 300 mm, 100 mm, and 1 mm; a 1 mm diameter hole is drilled at the center for the crack initiation. For minimum effect of sensor, we need smallest possible AE sensor such as PICO AE sensor. However, conventional acoustic emission sensors are resonant sensors. This implies that these sensors have strong resonances around the frequency it is designed for. This is good in general for detection of acoustic emissions even for low energy acoustic emissions. However, these resonating sensors may not be best to detect crack resonances as the signals detected by these sensors are modified by their own dynamics. Therefore, we use piezo electric wafer active sensors (PWAS) for detection of acoustic emissions during fatigue tests. One advantage of using PWAS is that it senses both in plane and out of plane motion, whereas PICO is predominantly sensitive to out of plane motion. Realistically, any contact type sensors will have its own dynamics which will influence the wave field that it senses. However, from Fig. 16 we can see that, for out of plane type motion, PWAS is much more sensitive in lower frequencies than PICO because PICO resonated at around 450 khz. This is advantageous for detection of crack resonances at lower frequencies. Therefore, in fatigue tests we rely on the PWAS sensor signal. We mount the specimen in MTS machine for fatigue testing and applied cyclic loading between 6.5 and 65% of the yield stress of the material (AL2024T4) to shorten the test duration.

41 Page 8 of 13 J Nondestruct Eval (2017) 36:41 Fig. 12 a Picture of the specimen with a slit; b excitation signal in time domain; c excitation signal in frequency domain We conduct the test in two stages. In the first stage we do not use any sensor or clay boundary on the specimen. We use higher frequency (10 12 Hz) of fatigue loading to shorten the duration of the test. In the second stage we use absorbing clay to absorb boundary reflections and used very low frequency fatigue loading (0.25 Hz) for higher degree of control over the crack growth. First we grow a long crack in the specimen (Fig. 17) and we mount the PWAS very close to the crack (Fig. 18). Then, the crack is grown further under low frequency fatigue loading. The reasons for such proximity of the PWAS are to sense the low amplitude crack resonances due to AE and the surface strains being very low close to a long crack. This ensures that the PWAS bonding on the plate surface did not break and the acoustic emissions detected by the PWAS corresponded to the crack growth are not due to cracking adhesive bonds. We use preamplifiers to amplify the signal detected by PWAS before recording. Figure 19 shows accumulative num- ber of acoustic emissions detected by the PWAS. This is consistent with the crack growth rate. As the crack grows longer, the growth rate increases resulting in higher rate of emissions. This can be easily understood from Fig. 19. Figure 20 shows typical signals received by PWAS related to crack growth. Predominantly we record two types of acoustic emission signals type 1 and type 2. If we compare type 1 signals with type 2 signals as shown in Fig. 20a and b, we can see that the type 1 signals appears to be non-dispersive and type 2 signals appear to be dispersive. Upon inspecting the tuning curves of PWAS in Fig. 20a and b we realize that the frequency contents of type 1 and type 2 signals are very similar to the tuning curves of PWAS [28] for S0 and A0 modes respectively. Also it is well known fact that S0 mode is non-dispersive and A0 mode is dispersive at relatively low frequencies. Therefore, we conclude that the type 1 and type

J Nondestruct Eval (2017) 36:41 Page 9 of 13 41 Fig. 13 Resonance of the slit at multiple frequencies due to acoustic emission from PWAS a measured at 20 mm from the slit, b e area scan results showing standing wave field around the slit Phenomen on Verified AE from Crack Crack Resonance Due to a Wideband Source at the Crack Tip AE from Crack Tip is a Wideband Source AE from Crack Tip Due to Crack growth AE from Crack Surface Due to Crack Vibration Capturing AE Signal from a Growing Crack Capturing AE Signal from Rubbing Crack Surfaces Challenges Types of AE Sources Fig. 14 Flow chart diagram for detection of fatigue crack length from acoustic emission Identify Crack Resonance Due to AE from Recorded AE Signals Determining Crack Length from Recorded AE Signal

41 Page 10 of 13 J Nondestruct Eval (2017) 36:41 Fig. 18 PWAS bonded next to a 20 mm long fatigue crack Fig. 15 a 100 mm wide, 300 mm long, and 1 mm thick specimen, b absorbing clay boundary to minimize boundary reflections Fig. 19 Cumulative number of acoustic emission recorded 2 signals correspond to the S0 and A0 Lamb wave modes respectively. A small percentage of signals appear to contain both S0 and A0 modes (Fig. 21). However, type 1 and type 2 signals account for more than 90% of acoustic emissions recorded with both of these types being present in equal proportions. We use Hanning window to isolate the Fig. 16 Tuning curve of sensors meaningful part of the signal from the noise floor then filtered the noise using 8 order low pass Butterworth filter of 800 khz. Since acoustic emissions due to fatigue crack growth occur within a very short time interval, the source should contain a wide frequency band. Therefore, based on the recorded acoustic emission signals, distinctive type 1 or type 2 signals are possible when the acoustic emission source is emitting either symmetric or antisymmetric modes respectively. So, there are two distinctive behaviors of the acoustic emission source represented by type 1 and type 2 signals. One possible explanation of this is, during the crack growth at the top of the loading cycle, the acoustic energy is released predominantly in S0 Lamb wave mode. Then, when loading cycles are decreasing, the inclined crack surfaces rub against each other near the crack tip and emit A0 Lamb wave mode. In Figs. 22a d and 23a d we can see samples of type 1 and type 2 signals at different stages of the test with different lengths of the fatigue crack. However, in the frequency plots of either of these two types of signals, we do not see any obvious crack resonance peak decreasing in frequency as the crack increased in length. If our explanation is correct, then the crack surfaces are not stress free when the A0 mode is emitted. So the bound- Fig. 17 20 mm long fatigue crack after 30,000 cycles of loading

J Nondestruct Eval (2017) 36:41 Page 11 of 13 41 Fig. 20 Acoustic emission signals received by PWAS and PWAS tuning: a type 1 and b type 2 Fig. 21 PWAS signal of mixed type ary conditions are unpredictable at the crack surfaces during this type of acoustic emissions. Therefore, using type 2 signals, we may not be able to predict crack length based on the crack resonance phenomenon which assumed stress free crack surfaces. At the top of the loading cycles, as the crack grows, the crack surfaces are stress free and we expect the generation of S0 mode. Therefore, using the crack resonance phenomenon we should be able to identify crack resonances from type 1 signals under ideal circumstances. However, there is also a possibility that our explanation is not correct because the proximity of the PWAS to the crack changes the crack resonance. This may also be the reason for the type 1 and 2 signals being very similar to the PWAS tuning curves. Fig. 22 Frequency content of PWAS signal of type 1 at four different crack lengths; a 20 mm; b 25 mm; c 30 mm; d 37 mm

41 Page 12 of 13 J Nondestruct Eval (2017) 36:41 Fig. 23 Frequency content of PWAS signal of type 2 at four different crack length of a 20 mm; b 25 mm; c 30 mm; d 37 mm 7 Conclusion and Future Work In this paper we have presented a study to understand the behavior of fatigue crack as a source of acoustic emission based on physics of wave propagation. We have used FE analysis to develop this understanding. We have extended the point source model suggested by Hamstad et al. [26]toa line source to simulate acoustic emission due to fatigue crack growth in a thin plate. We have demonstrated the effective use of non-reflective boundaries to absorb boundary reflection in AE simulation using a small and efficient 3D model. Similarly, we have demonstrated the effective use of absorbing clay boundaries to absorb boundary reflections for clear identification of AE signals during fatigue tests. We have also presented a unique phenomenon of crack vibration due to acoustic emissions and verified it experimentally. Based on this phenomenon we have proposed a method to detect the crack length from the recorded acoustic emission signals containing crack resonance information. However, detecting crack length of a growing fatigue crack during a fatigue test remains challenging. The main challenge in detecting crack resonance using a finite sensor is the dominance of the sensor dynamics over the local resonance field of the crack. Acknowledgements Supports from the Office of Naval Research #N000141110271, N000141410655, Dr. Ignacio Perez (Program Officer) is thankfully acknowledged. References 1. Roberts, T.M., Talebzadeh, M.: Acoustic emission monitoring of fatigue crack propagation. J. Constr. Steel Res. 59(6), 695 712 (2003) 2. Chang, H., Han, E.H., Wang, J.Q., Ke, W.: Acoustic emission study of fatigue crack closure of physical short and long cracks for aluminum alloy LY12CZ. Int. J. Fatigue 31(3), 403 407 (2009) 3. Gagar, D., Foote, P., Irving, P.: A novel closure based approach for fatigue crack length estimation using the acoustic emission technique in structural health monitoring applications. Smart Mater. Struct. 23(10), 105033 (2014) 4. Cuadra, J., Vanniamparambil, P.A., Servansky, D., Bartoli, I., Kontsos, A.: Acoustic emission source modeling using a datadriven approach. J. Sound Vib. 341, 222 236 (2015) 5. Paris, P., Erdogan, F.: A critical analysis of crack propagation laws. J. Fluids Eng. 85(4), 528 534 (1963) 6. Nemati, N., Metrovich, B., Nanni, A.: Acoustic emission assessment of through-thickness fatigue crack growth in steel members. Adv. Struct. Eng. 18(2), 269 283 (2015) 7. Ceranogliu, A.N., Yih-Hsing, P.: Propagation of elastic pulses and acoustic emission in a plate. J. Appl. Mech. 48, 125 147 (1981) 8. Chung, J.-B., Kannatey-Asibu, E.: Acoustic emission from plastic deformation of a pure single crystal. J. Appl. Phys. 72(5), 1812 (1992) 9. Lysak, M.V.: Development of the theory of acoustic emission by propagating cracks in terms of fracture mechanics. Eng. Fract. Mech. 55(3), 443 452 (1996) 10. Andreykiv, O., Skalsky, V., Serhiyenko, O., Rudavskyy, D.: Acoustic emission estimation of crack formation in aluminium alloys. Eng. Fract. Mech. 77(5), 759 767 (2010) 11. Andreykiv, O.Y., Lysak, M.V., Serhiyenko, O.M., Skalsky, V.R.: Analysis of acoustic emission caused by Internal cracks. Eng. Fract. Mech. 68(11), 1317 1333 (2001) 12. Sause, M.G.R., Richler, S.: Finite element modelling of cracks as acoustic emission sources. J. Nondestruct. Eval. 34(1), 4 (2015) 13. Sause, M.G.R., Horn, S.: Simulation of acoustic emission in planar carbon fiber reinforced plastic specimens. J. Nondestruct. Eval. 29(2), 142 (2010) 14. Gonzalez, C., LLorca, J.: Multiscale modeling of fracture in fiberreinforced composites. Acta Mater. 54(16), 4171 4181 (2006) 15. Hu, W., Ha, Y.D., Bobaru, F.: Modeling dynamic facture and damage in a fiber-reinforced composite lamina with peridynamics. J. Multiscale Comput. Eng. 9(6), 707 726 (2011) 16. Gorman, M.R., Ziola, S.M.: Plate waves produced by transverse matrix cracking. Ultrasonics 29(3), 245 251 (1991)

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